April 2025
Intermediate to advanced
268 pages
6h 17m
Portuguese (Portugal, Brazil)
Content preview from Algoritmos de grafos
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Capítulo 6. Algoritmos de deteção de comunidades
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A formação de comunidades é comum em todos os tipos de redes, e a sua identificação é essencial para avaliar o comportamento do grupo e os fenómenos emergentes. O princípio geral para encontrar comunidades é que os seus membros terão mais relações dentro do grupo do que com nós fora do seu grupo. A identificação destes conjuntos relacionados revela aglomerados de nós, grupos isolados e a estrutura da rede. Esta informação ajuda a inferir comportamentos ou preferências semelhantes de grupos de pares, a estimar a resiliência, a encontrar relações aninhadas e a preparar dados para outras análises.
Apresentaremos pormenores sobre os algoritmos de deteção de comunidades mais representativos:
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Contagem de triângulos e coeficiente de agrupamento para a densidade global das relações
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Componentes fortemente conectados e componentes fracamente conectados para encontrar clusters conectados
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Propagação de etiquetas para inferir rapidamente grupos com base em etiquetas de nós
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Louvain Modularidade para analisar a qualidade e as hierarquias dos agrupamentos
Explicaremos como funcionam os algoritmos e mostraremos exemplos no Apache Spark e no Neo4j. Nos casos em que um algoritmo só está disponível numa plataforma, apresentaremos apenas um exemplo. Utilizamos relações ponderadas para estes algoritmos porque são normalmente ...
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